A cortical sparse distributed coding model linking mini- and macrocolumn-scale functionality

TL;DR

This paper proposes a unified cortical model where minicolumns enforce sparse coding within macrocolumns, enabling fast recognition and storage of inputs through a winner-take-all mechanism influenced by input familiarity.

Contribution

It introduces a novel model linking minicolumn function to macrocolumnar sparse coding, with an algorithm for rapid input recognition and a proposed neural circuitry mapping.

Findings

Minicolumns act as winner-take-all modules enforcing sparse codes.

The model achieves ultra-fast storage and retrieval of similar inputs.

Familiarity modulates the randomness in code activation, enhancing efficiency.

Abstract

No generic function for the minicolumn, i.e., one that would apply equally well to all cortical areas and species, has yet been proposed. I propose that the minicolumn does have a generic functionality, which only becomes clear when seen in the context of the function of the higher-level, subsuming unit, the macrocolumn. I propose that: a) a macrocolumn's function is to store sparse distributed representations of its inputs and to be a recognizer of those inputs; and b) the generic function of the minicolumn is to enforce macrocolumnar code sparseness. The minicolumn, defined here as a physically localized pool of ~20 L2/3 pyramidals, does this by acting as a winner-take-all (WTA) competitive module, implying that macrocolumnar codes consist of ~70 active L2/3 cells, assuming ~70 minicolumns per macrocolumn. I describe an algorithm for activating these codes during both learning and retrievals, which causes more similar inputs to map to more highly intersecting codes, a property which yields ultra-fast (immediate, first-shot) storage and retrieval. The algorithm achieves this by adding an amount of randomness (noise) into the code selection process, which is inversely proportional to an input's familiarity. I propose a possible mapping of the algorithm onto cortical circuitry, and adduce evidence for a neuromodulatory implementation of this familiarity-contingent noise mechanism. The model is distinguished from other recent columnar cortical circuit models in proposing a generic minicolumnar function in which a group of cells within the minicolumn, the L2/3 pyramidals, compete (WTA) to be part of the sparse distributed macrocolumnar code.